Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.).

For all traits and cycles, genotypic and genotype × location.tester (σ g×l 2 ) variance components were highly significant ( p < 0.01) and estimates of σ g×l 2 were always smaller than the genotypic variance component.

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